TY - GEN
T1 - NursingLLM
T2 - 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp Companion 2025
AU - She, Dong
AU - Ren, Junbin
AU - Sun, Yueru
AU - Zhang, Wenbo
AU - Gao, Yang
AU - Jin, Zhanpeng
N1 - Publisher Copyright:
© 2025 ACM.
PY - 2025/12/29
Y1 - 2025/12/29
N2 - Elderly individuals in nursing homes often experience loneliness and health-related anxiety. To explore how LLM-based chatbots might support this population, we conducted in-depth interviews with 23 elderly residents to understand their emotional and informational needs. Based on these findings, we designed and implemented NursingLLM, a conversational agent tailored for aging-related health support. Guided by principles from HCI and gerontology, the system emphasizes ease of use, trust-building, and empathetic interaction. NursingLLM integrates a multimodal (voice and text) interface to improve accessibility, Retrieval-Augmented Generation (RAG) to provide verifiable health information, and prompting strategies to sustain natural and caring conversations. We then conducted a preliminary user study with 16 residents in two care centers to assess usability and perceived supportiveness. Results suggest that NursingLLM helped users better understand their symptoms, recall daily care routines, and feel more emotionally supported. This work offers design insights and a system prototype for future AI-driven tools to promote older adults' well-being in institutional settings.
AB - Elderly individuals in nursing homes often experience loneliness and health-related anxiety. To explore how LLM-based chatbots might support this population, we conducted in-depth interviews with 23 elderly residents to understand their emotional and informational needs. Based on these findings, we designed and implemented NursingLLM, a conversational agent tailored for aging-related health support. Guided by principles from HCI and gerontology, the system emphasizes ease of use, trust-building, and empathetic interaction. NursingLLM integrates a multimodal (voice and text) interface to improve accessibility, Retrieval-Augmented Generation (RAG) to provide verifiable health information, and prompting strategies to sustain natural and caring conversations. We then conducted a preliminary user study with 16 residents in two care centers to assess usability and perceived supportiveness. Results suggest that NursingLLM helped users better understand their symptoms, recall daily care routines, and feel more emotionally supported. This work offers design insights and a system prototype for future AI-driven tools to promote older adults' well-being in institutional settings.
KW - conversational agents
KW - elderly care
KW - health information seeking
KW - human-centered ai
KW - retrieval-augmented generation
UR - https://www.scopus.com/pages/publications/105027082995
U2 - 10.1145/3714394.3756349
DO - 10.1145/3714394.3756349
M3 - 会议稿件
AN - SCOPUS:105027082995
T3 - UbiComp Companion 2025 - Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing
SP - 1633
EP - 1639
BT - UbiComp Companion 2025 - Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing
A2 - Beigl, Michael
A2 - Jacucci, Giulio
A2 - Sigg, Stephan
A2 - Xiao, Yu
A2 - Bardram, Jakob E.
A2 - Tsiropoulou, Eirini Eleni
A2 - Xu, Chenren
PB - Association for Computing Machinery, Inc
Y2 - 12 October 2025 through 16 October 2025
ER -
